Put the ipynb file and html file in the github branch you created in the last assignment and submit the link to the commit in brightspace
from plotly.offline import init_notebook_mode
import plotly.io as pio
import plotly.express as px
init_notebook_mode(connected=True)
pio.renderers.default = "plotly_mimetype+notebook"
#load data
df = px.data.gapminder()
df.head()
| country | continent | year | lifeExp | pop | gdpPercap | iso_alpha | iso_num | |
|---|---|---|---|---|---|---|---|---|
| 0 | Afghanistan | Asia | 1952 | 28.801 | 8425333 | 779.445314 | AFG | 4 |
| 1 | Afghanistan | Asia | 1957 | 30.332 | 9240934 | 820.853030 | AFG | 4 |
| 2 | Afghanistan | Asia | 1962 | 31.997 | 10267083 | 853.100710 | AFG | 4 |
| 3 | Afghanistan | Asia | 1967 | 34.020 | 11537966 | 836.197138 | AFG | 4 |
| 4 | Afghanistan | Asia | 1972 | 36.088 | 13079460 | 739.981106 | AFG | 4 |
Recreate the barplot below that shows the population of different continents for the year 2007.
Hints:
df_year = df.groupby(['continent','year']).sum(numeric_only = True).reset_index()
df_2007 = df_year[df_year['year']==2007]
fig = px.bar(df_2007, x="pop", y="continent", color="continent",
hover_name="pop",width=950,height=450)
fig.update_layout(showlegend=False)
fig.show()
# YOUR CODE HERE
df_year = df.groupby(['continent','year']).sum(numeric_only = True).reset_index()
df_2007 = df_year[df_year['year']==2007]
fig = px.bar(df_2007, x="pop", y="continent", color="continent",
hover_name="pop",width=950,height=450)
fig.update_layout(showlegend=False)
fig.update_yaxes(categoryorder='total ascending')
fig.show()
# YOUR CODE HERE
Add text to each bar that represents the population
fig = px.bar(df_2007, x="pop", y="continent", color="continent",
hover_name="pop",text='pop',width=950,height=450)
fig.update_layout(showlegend=False)
fig.update_traces(texttemplate='%{text:.2s}')
fig.update_yaxes(categoryorder='total ascending')
fig.show()
# YOUR CODE HERE
Thus far we looked at data from one year (2007). Lets create an animation to see the population growth of the continents through the years
fig = px.bar(df_year, x="pop", y="continent", color="continent",
hover_name="pop",width=950,height=450,animation_frame='year',range_x=[0,4e9])
fig.update_layout(showlegend=False)
fig.update_yaxes(categoryorder='total ascending')
fig.show()
# YOUR CODE HERE
Instead of the continents, lets look at individual countries. Create an animation that shows the population growth of the countries through the years
fig = px.bar(df, x="pop", y="country", color="country",
hover_name="pop",width=950,height=450,animation_frame='year',range_x=[0,1.5e9])
fig.update_layout(showlegend=False)
fig.update_yaxes(categoryorder='total ascending')
fig.show()
# YOUR CODE HERE
Clean up the country animation. Set the height size of the figure to 1000 to have a better view of the animation
fig = px.bar(df, x="pop", y="country", color="country",
hover_name="pop",width=950,height=1000,animation_frame='year',range_x=[0,1.5e9])
fig.update_layout(showlegend=False)
fig.update_yaxes(categoryorder='total ascending')
fig.show()
# YOUR CODE HERE
# YOUR CODE HERE
#no idea how to do this using axis limits, no amount of online searches helped
top_10_countries = df.groupby('country')['pop'].max().sort_values(ascending=False).head(10).index
df_top_10 = df[df['country'].isin(top_10_countries)]
fig = px.bar(df_top_10, x="pop", y="country", color="country",
hover_name="pop",width=950,height=500,animation_frame='year',range_x=[0,1.5e9],category_orders={"country": top_10_countries})
fig.update_layout(showlegend=False)
fig.update_yaxes(categoryorder='total ascending')
fig.show()